activity
20242026
collaborators

7 papers

cs.CV2026

FORGE: Fine-grained Multimodal Evaluation for Manufacturing Scenarios

Xiangru Jian, Hao Xu, Wei Pang +13

The manufacturing sector is increasingly adopting Multimodal Large Language Models (MLLMs) to transition from simple perception to autonomous execution, yet current evaluations fai…

cs.CV2025

Paper2Poster: Towards Multimodal Poster Automation from Scientific Papers

Wei Pang, Kevin Qinghong Lin, Xiangru Jian +2

Academic poster generation is a crucial yet challenging task in scientific communication, requiring the compression of long-context interleaved documents into a single, visually co…

cs.CV2025

The Underappreciated Power of Vision Models for Graph Structural Understanding

Xinjian Zhao, Wei Pang, Zhongkai Xue +6

Graph Neural Networks operate through bottom-up message-passing, fundamentally differing from human visual perception, which intuitively captures global structures first. We invest…

cs.DB2025

LazyVLM: Neuro-Symbolic Approach to Video Analytics

Xiangru Jian, Wei Pang, Zhengyuan Dong +2

Current video analytics approaches face a fundamental trade-off between flexibility and efficiency. End-to-end Vision Language Models (VLMs) often struggle with long-context proces…

cs.CV2025

DREAM: Improving Video-Text Retrieval Through Relevance-Based Augmentation Using Large Foundation Models

Yimu Wang, Shuai Yuan, Bo Xue +4

Recent progress in video-text retrieval has been driven largely by advancements in model architectures and training strategies. However, the representation learning capabilities of…

cs.LG2025

Enhancing Graph Self-Supervised Learning with Graph Interplay

Xinjian Zhao, Wei Pang, Xiangru Jian +3

Graph self-supervised learning (GSSL) has emerged as a compelling framework for extracting informative representations from graph-structured data without extensive reliance on labe…